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Summary
One of the biggest concerns researchers have when having any designer or product manager conduct their own research is that they'll ask biased or bad questions. In theory bad research done by a product team should be accountable to them but since there's a team named "research," that can inevitably fallback on us. We've all offered training to teams at some point but you can lead a horse to water but not force them to drink. Enter AI - your partners will want to use it because it helps them get something they don't usually do (write discussion guides) faster and by writing custom Gems or GPTs, the research team can keep consistency, ensure the AI pushes back in the right way for quality, etc. In this session, I'll cover how to build these and the instruction sets I provide to the tools.
Key Insights
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Custom AI GPTs can provide guardrails to help non-researchers conduct higher-quality user research.
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Splitting AI tools into multiple specialized GPTs prevents context overload and hallucinations.
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Researchers save over 80% of their time by using AI to support routine research planning and execution.
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Automating recruitment and incentive tracking through Google Sheets and Zapier reduces manual effort.
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AI can improve research consistency by enforcing unbiased question guidelines and avoiding leading or double-barreled questions.
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Limitations remain in AI’s ability to synthesize large transcript sets and provide fully accurate quotes.
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Democratizing research allows product managers and designers to engage more closely with customers while researchers focus on strategic insights.
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Avoiding shadow AI tools is critical for organizational security and compliance.
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Video analysis and unmoderated usability testing can now be partially automated using custom GPT Gems.
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The future of UX research may shift toward researchers providing ‘forest-level’ insights while PMs/designers handle ‘tree-level’ tactical research.
Notable Quotes
"We call ourselves a B2C CRM: helping businesses connect to their consumers and keep the relationship going."
"Before AI, research teams spent over a quarter of their time consulting about research questions, often repeating themselves."
"One of my biggest pet peeves is biased questions; I hate the term validation, I prefer evaluation."
"If we’re not helping with the decision, why are they paying us what they’re paying us? That’s the essence of research."
"We want to make sure researchers spend one hour in office hours, not eight to twelve hours a week helping others."
"Designers and product managers often want more control, and custom AI gives them that in research tasks."
"The tools are meeting people where they’re already going: ChatGPT or Gemini, rather than forcing new platforms."
"Shadow AI usage is a huge security risk in public companies and should be managed by IT and leadership."
"We ask our AI assistants to explicitly avoid leading and double-barreled questions to ensure unbiased research."
"The future is researchers painting the larger picture while PMs and designers focus on deep, tactical user insights."
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